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Java 8 vs Java 11 vs Java 21
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Java 8 : Lamda expressions, Functional Interfaces, Default and Static interfaces, Streams, Completable features and New Date and time functions are introduced
Java 11 : Local Variable syntax changes in Lamda, Enhanced Streams and Collections concepts and HttpClient is introducted
Java 17 :
Java 21 : Virtual Threads, Pattern Matching in switch, Record Patterns and SequencedCollection are introduced
Java 25 : Collection Performance, Stream preformance, Concurrent & Runtime Performance and I/O Security Enhancements.
Immutable Class : A class which is not having setters and who's instance cannot be change after they are created.
- Declaring a final class
- Make all fields are private
- Make all fields are final.
- Donot provide the setters.
- Thread safety
- Security & Consistency
- Reliable Hash keys
Multithreading :
CompletableFuture vs Future :
- supplyAsync() — starting async tasks the right way (Java 8 CompletableFuture supplyAsync example)
- thenApply() & thenAccept() — transforming and consuming results (Multiple chained Futures cannot combined together using Future)
- thenCombine() — combining two futures into one (Multiple futures cannot combined together)
- exceptionally() — exception handling in CompletableFuture (Poor exception handling in Future)
- Chaining of futures vs combining futures — when to use each
Executor Service :
Virtual Threads :
- Higher Concurrency
- Lower Memory Overhead
- Better scalability for I/O bound operations
- API Gateway Parllel processing of larger datasets.
- Real time Systems like Chat applicatoins, Live Updates, Trackers
- I/O Bound operations like Database calls, HTTP requests, file Operations
- Handles millions of Concurrent Request.
Microservices Design Patterns :
Circuit Breaker DP :
Circuit breaker implemented using Resillance4J and it has 3 components : CLOSED, OPEN and HALF-OPEN.
CLOSED : When failure rate threshold is below
OPEN : When failture rate threshold is above
HALF-OPEN : After wait durtaion it will go to HALF-OPEN
Circuit breaker uses two types of sliding windows to store and aggregate the outcome of calls.
1. Count based sliding window
2. Time-based sliding window
Bulk Head Pattern : 2 types of SemaphoreBulkhead and FixedThreadPoolBulkhead
Rate Limtter Design Pattern : Rate limiting is an imperative technique to prepare your API for scale and establish high availability and reliability of your service.
Retry Design Pattern : Just like the CircuitBreaker module, this module provides an in-memory RetryRegistry which you can use to manage (create and retrieve) Retry instances.
Saga Design Pattern :
Event Driven Approach Design Pattern :
- Kafka based event driven approach
Database Design Pattern :
Indentity Design Pattern : Security Identity Management (verifying who is making requests) and Domain Data Identity (how data entities maintain their identifiers across service boundaries)
Feign Client vs Rest Client :
The primary difference is that Feign Client is declarative (you write an interface and let the framework generate the HTTP code), while a Rest Client is programmatic/fluent (you manually write the steps to build and execute the request).
Microservice vs Monolithic :
A monolithic architecture consolidates all software components into a single program, whereas a microservices architecture divides the application into separate, self-contained services.
Microservices are advantageous for certain types of projects:
Complex Systems
Scalability
Technology Diversification
Autonomous Teams: For bigger organizations with multiple teams that need to work independently.
- Database per service
- Data inconsistency
- Integrate Testing
- Synchronous
- Asynchronous
- Restful api's
- Event Based communication
- Database per service
- API-Gateway
How would you decompose a monolithic application into microservices?
- Identify Domains
- Service Boundaries
- Data Segrigation
- Decouple services
Kafka Based Interview Questions :
Kafka consumer vs Consumer Group :
- Kafka consumer reads the data from the topic
- Consumer group is a set of consumers work together and reads one or more topics.
- Offset is a unique sequential identifier record with in a partition.
- Kafka tracks the offset per partition, per consumer group. So each group can consumes its own position.
- Retention can be time based, once it reaches to limit old message will be discarded.
- Retention limit will be provided while creating the kafka clusters.
- Replication : Each partition is replicated across the mulitple brokers
- Acknowlegements : Producers can wait for leaders only
- Atomic, orders writes to a partition
- Idempotent producers to prevent duplicate writes on retry.
- To manage the metadata management kafka introduced the KRaft by removing the dependency on Apache ZooKeeper.
- Increase the Partition count
- Add more consumers instances :
- Ensure 1:1 Ratio : Align the no of active consumers with no of topic partitions.
Streams
- Run's single thread and results are predictable
- Sequential
- Low overheaded
- Run's on multi threaded and results are unpredictable.
- Parllel
- High Overheaded due to thread management.
Map vs Flat Map :
- One to one mapping
- To use basic data transformation
- One to Many (zero)mapping
- To handling collection of collections
- CodeBase
- Dependencies
- Configuration
- Backing services
- Build, Release, Run
- Processes
- Port Binding
- Concurrency
- Disposability
- Dev/Prod Parity
- Logs
- Admin Process
AWS Interview Questions :
3 Types of Cloud Computing :
- SAAS (Software as a service) : Aws email service etc services by AWS.
- PAAS (Platform as a service) : Elastic Beanstalk, Heroko.
- IAAS (Infrastructure as a service) : EC2 instance, S3 Storage, VPC.
- Scalable virtual servers called instances in AWS
- EC2 instances are used to host websites
- Run batch job process to acheive scalability
S3 Storage :
- Simple Storage Service
- Stores the objects in secure way
- Identity Access Management
- Helps you to securely access to AWS services
- IAM allows us to manage users & Roles.
- Relational Database Service
- To Manage the database service
- Virtual Private Network
- To create a virtual network in AWS.
- Uses for monitoring purposes
- Metrics, Alarms, Logs, Events
- Server less Compute service
- Blue means current version deployment
- Green means new version deployment
- Replacement to kubernetes, this simplifier to run EC2 Instances.
- Must follow the 7 Rs Framework
- Rehost
- Replatform
- Repurchase
- Refactor
- Retire
- Retain
- Relocate
- Used EC2 and RDS to migrate also important.
DataStructures :
- Array
- String
- Linked List
- Queue
- Stack
- Tree
- Graph
- Hashing
SpringBoot ::
- Singleton
- Prototype
- Request
- Session
- Application
- Websocket
Examples: Invalid account number, Insufficient balance, Payment failed, Flight not found
Serilization vs De-Serialization ::
HashMap Internally working technique ::
When we will do the HashCode and Equals() :
when ever both the string object values are same then we will use hashcode and equals().
What is a functional interface?
A functional interface has exactly one abstract method and can be used as the target of a lambda or method reference.
why are Streams usually faster than loops for large data?
Streams use internal optimizations like: Stream Pipeline
• Lazy ovaluation
• Mothod chaining
•Built-in parallel proconcing
Syncrnonization ::
Bad practise of synchronization : synchronizing on the boxed type Integer:
private int count = 0;
private final Integer intLock = count; // the solution for synchronization on the boxed primitive is to create a new instance. private final Integer intLock = new Integer(count);
public void boxedPrimitiveBadPractice() {
synchronized (intLock) {
count++;
// ...
}
}
Why does HashMap allow one null key and multiple null values ?
HashMap is docignod to handle null gracofully. It treats null key's hashCode as O and stores it in bucket O. Multiple null values are allowed because values are not used in hashing or key comparison.
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